Synergistic hyperactivation of both mTORC1 and mTORC2 underlies the neural abnormalities of PTEN-deficient human neurons and cortical organoids
Bibliographic record
Abstract
Mutations in the phosphatase and tensin homolog (PTEN) gene are associated with severe neurodevelopmental disorders. Loss of PTEN leads to hyperactivation of the mechanistic target of rapamycin (mTOR), which functions in two distinct protein complexes, mTORC1 and mTORC2. The downstream signaling mechanisms that contribute to PTEN mutant phenotypes are not well delineated. Here, we show that pluripotent stem cell-derived PTEN mutant human neurons, neural precursors, and cortical organoids recapitulate disease-relevant phenotypes, including hypertrophy, electrical hyperactivity, enhanced proliferation, and structural overgrowth. PTEN loss leads to simultaneous hyperactivation of mTORC1 and mTORC2. We dissect the contribution of mTORC1 and mTORC2 by generating double mutants of PTEN and RPTOR or RICTOR, respectively. Our results reveal that the synergistic hyperactivation of both mTORC1 and mTORC2 is essential for the PTEN mutant human neural phenotypes. Together, our findings provide insights into the molecular mechanisms that underlie PTEN-related neural disorders and highlight novel therapeutic targets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".